Skip to content

Release notes#

Latest changes (unreleased)#

Features#

Improvements#

Fixes#

0.8.1#

Adding missing wheels for macos, no changes to the library

0.8.0#

Features#

  • Add EventSet.moving_product() and EventSet.cumprod() operators. @akshatvishu
  • Add to.to_numpy(). @nagavenkateshgavini
  • Add trigonometric functions EventSet.arccos(), EventSet.arcsin(), EventSet.arctan(), EventSet.cos(), EventSet.sin(), and EventSet.tan(). @akshatvishu

Improvements#

  • Speed up of calendar operations (now implemented in c++)
  • Add force_garbage_collector_interval to tp.compile.
  • Improved worst case time complexity from quadratic to linear for moving min/max operator.
  • Show first and last events instead of only first ones when displaying an EventSet. @jtaylor205
  • Exposed tp.FeatureSchema and tp.IndexSchema
  • EventSet.propagate now works even if both arguments don't have the same index values.
  • Add font_scale param to tp.plot
  • Speed-up tp.plot on evsets with a large number of index values.
  • tp.plot now works even when evsets have different index values.
  • Allow tp.from_tensorflow_record to consume a list of paths.
  • Add parameters num_parallel_reads and buffer_size to tp.from_tensorflow_record.
  • Check that timestamps are sorted on tp.from_tensorflow_record

Fixes#

  • Fixed a bug with EventSet.tick_calendar and daylight savings time.
  • Fixed a bug with calendar operations and daylight savings time.

Thanks#

In adition to the contributors mentioned above, thanks to @umbr4g3, @jsoref, and @tanaysd for improvements to the Github Actions and profiling.

0.7.0#

Features#

  • Add tp.from_parquet() and tp.to_parquet().
  • Add EventSet.fillna() operator.

Improvements#

  • Add support for pip build on Windows.
  • Documentation improvements.
  • Add timestamps parameter to tp.from_pandas().
  • Add implicit casting in EventSet.where() operator.
  • Add support for list argument in EventSet.rename() operator.

0.1.6#

Features#

  • Support for timezone argument in all calendar operators.
  • Add drop() operator to drop features.
  • Add assign() operator to assign features.
  • Add before() and after() operators.

Improvements#

  • Improve error messages for type mismatch in window operators.
  • Improve structure of docs site.
  • Support exporting timestamps as datetimes in tp.to_pandas().
  • Remove inputs limit in glue() and combine().

Fixes#

  • Use wday=0 for Mondays in tick_calendar (like calendar_day_of_week).
  • Support bool in DType.missing_value().
  • Show EventSet's magic methods in docs.

0.1.5#

Features#

  • Added EventSet.filter_moving_count() operator.
  • Added EventSet.map() operator.
  • Added EventSet.tick_calendar() operator.
  • Added EventSet.where() operator.
  • Added all moving window operators to Beam execution backend.

Improvements#

  • Print EventSet timestamps as datetimes instead of float.
  • Support sampling argument in EventSet.cumsum() operator.
  • Using utf-8 codec to support non-ascii in string values.
  • New tp.types module to facilitate access to types used throughout the API.
  • Relaxed version requirements for protobuf and pandas.

Fixes#

  • Fixed issues when loading timestamps from np.longlong and other dtypes.

0.1.4#

Features#

  • Added EventSet.select_index_values() operator.
  • Added steps argument to EventSet.since_last() operator.
  • Added variable window_length option to moving window operators.
  • Added unsupervised anomaly detection tutorial.
  • Add until_next operator.
  • Added Beam execution tutorial.
  • Added changelog to docs site.

Improvements#

  • Added display_max_feature_dtypes and display_max_index_dtypes options to tp.config.
  • Improved HTML display of an EventSet.
  • Improvements in Beam execution backend.

Fixes#

  • Fixed tutorials opening unreleased versions of the notebooks.

0.1.3#

This is the first operational version of Temporian for users. The list whole and detailed list of features is too long to be listed. The main features are:

Features#

  • PyPI release.
  • 72 operators.
  • Execution in eager, compiled mode, and graph mode.
  • IO Support for Pandas, CSV, Numpy and TensorFlow datasets.
  • Static and interactive plotting.
  • Documentation (3 minutes intro, user guide and API references).
  • 5 tutorials.